Creating a Pandas Series from Dictionary
A Pandas Series is a one-dimensional labeled array capable of holding any data type (integers, strings, floating point numbers, Python objects, etc.). It has to be remembered that, unlike Python lists, a Series will always contain data of the same type. Letâs see how to create a Pandas Series from Python Dictionary.
Pandas Series from Dictionary
In this article, you will learn about the different methods of configuring the pandas.Series() command to make a pandas series from a dictionary followed by a few practical tips for using them.
Using Series() method without index parameter
In this case, dictionary keys are taken in a sorted order to construct the index.
Example 1: Dictionary keys are given in sorted order.
Python3
# import the pandas lib as pd import pandas as pd # create a dictionary dictionary = { 'A' : 10 , 'B' : 20 , 'C' : 30 } # create a series series = pd.Series(dictionary) print (series) |
A 10 B 20 C 30 dtype: int64
Example 2: Dictionary keys are given in unsorted order.
Python3
# import the pandas lib as pd import pandas as pd # create a dictionary dictionary = { 'D' : 10 , 'B' : 20 , 'C' : 30 } # create a series series = pd.Series(dictionary) print (series) |
B 20 C 30 D 10 dtype: int64
Using Series() method with index parameter
In this case, the values in data corresponding to the labels in the index will be assigned.
Example 1: An index list is passed of the same length as the number of keys present in the dictionary.
Python3
# import the pandas lib as pd import pandas as pd # create a dictionary dictionary = { 'A' : 50 , 'B' : 10 , 'C' : 80 } # create a series series = pd.Series(dictionary, index = [ 'B' , 'C' , 'A' ]) print (series) |
B 10 C 80 A 50 dtype: int64
Example 2: An index list is passed of greater length than the number of keys present in the dictionary, In this case, Index order is persisted and the missing element is filled with NaN (Not a Number).
Python3
# import the pandas lib as pd import pandas as pd # create a dictionary dictionary = { 'A' : 50 , 'B' : 10 , 'C' : 80 } # create a series series = pd.Series(dictionary, index = [ 'B' , 'C' , 'D' , 'A' ]) print (series) |
B 10 C 80 D NaN A 50 dtype: float64
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